Most biological processes involve large-scale changes in gene expression levels and/or patterns. The advent of microarray technology has made it possible to study these changes in expression in order to identify new complex phenotypic markers or to identify genes involved in particular cellular processes.
The application of microarray technologies is limited by the need for large amounts of RNA; RNA equivalent to the amount present in hundreds of thousands, or even millions, of cells is needed for robust analysis. The requirement of large amounts of RNA precludes the use of microarray technology for the analysis of biological events involving fewer than hundreds of thousands of cells. Thus, gene expression changes in clonal events, such as tumor development and metastasis, as well as multiple small-scale gene expression changes (e.g., as in a heterogeneous tumor), cannot be analyzed. Similarly, processes involving the maturation of a few or single cells, such as the differentiation of stem and germ cells, are out of the grasp of microarray technology.
To overcome problems associated with small amounts of RNA, amplification of RNA samples is frequently performed. Amplification of small amounts of RNA invariably involves a reverse transcription step, followed by either a linear amplification such as the antisense RNA amplification protocol (see, e.g., van Gelder, R. N. et al., PNAS USA 87(5):1663-7 (1990); Everwine, J., Biotechniques 20(4):584-91 (1996) by an exponential amplification using a polymerase chain reaction (PCR)-mediated amplification (rt-PCR). Both linear and exponential amplification approaches have been used to amplify RNA for microarray analysis (Kacharmina, J. E. et al., Methods Enzymol. 303(-HD):3-18 (1999); Spirin, K. S. et al., Invest. Ophthalmol. Vis. Sci. 40(13):3108-15 (1999)). Accurate quantification of rt-PCR-amplified gene pools is problematic because of differences in relative amplification efficiencies between RNA transcripts, attributable to many factors (e.g., length of the transcript, secondary structure constrictions and GC content), which can lead to distortion of relative amounts of RNA transcripts in a sample.
The present invention is drawn to methods for determining the amount of RNA transcripts in a test sample. The methods utilize a reference sample comprising a known amount of a reference nucleic acid; the reference nucleic acid is labeled with a first strand 3xe2x80x2 cDNA primer and a first strand 5xe2x80x2 cDNA primer comprising a reference specificity determining box. A test sample comprising an amount of test RNA (e.g., containing a particular RNA transcript of interest) is similarly labeled with the same first strand 3xe2x80x2 cDNA primer and with a first strand 5xe2x80x2 cDNA primer comprising a test specificity determining box. In a preferred embodiment, the 5xe2x80x2 cDNA primers contain a partial RNA polymerase promoter sequence (e.g., a partial T7 RNA polymerase promoter sequence), a polyT sequence, and a specificity determining box (either reference or test) between the partial RNA polymerase promoter sequence and the polyT sequence.
The reference sample and the test sample are admixed and subjected to polymerase chain reaction amplification conditions, followed by division of the amplified, mixed sample and continued amplification (such as by PCR or linear extension) of the divided sample using continued amplification primers that specifically bind to either the reference specificity determining box or the test specificity determining box. The resultant nucleic acids contain amplified reference nucleic acid or amplified cDNA of the test RNA, from which cRNA can be made by in vitro transcription. The amount of the test RNA, or of a particular RNA transcript of interest in the sample, can be correlated with a ratio of the amount of amplified cDNA of the test RNA (or RNA transcript of interest in the amplified cDNA of the test RNA) over the amount of the amplified reference nucleic acid, multiplied by the known amount of the reference nucleic acid in the reference sample.
The methods of the invention can be used to facilitate accurate assessment of RNA transcripts in small samples. The methods are simple and less costly than antisense-RNA based methodologies, and provide an added measure of confidence in identifying the presence or absence of gene expression in small samples. Furthermore, the methods allow the use of microarray-based analysis for small RNA samples.